ML researcher and data scientist working across clinical and scientific AI
Reinforcement learning, medical AI, scientific computing, and LLM tooling
I am Thomas Virdis, also known as CTCycle. I build open-source tools for clinical and scientific workflows. My work includes reinforcement learning, medical computer vision, LLM tooling, computational chemistry, and data analysis.
I currently work as a Senior Data Scientist and ML Engineer at Inmatica S.p.A. My background combines a bachelor's and master's in Biotechnology from the University of Genoa with a PhD in Engineering Sciences from the Vrije Universiteit Brussel.
During my PhD, I worked on the CheckPack project, developing micro-sensors to detect food spoilage and monitor quality in real time. That experience connected experimental research with data analysis and machine learning.
Research application for roulette training and inference experiments. It includes a DQN agent, a PyTorch training pipeline, a FastAPI backend, a React frontend, and a Tauri desktop shell.
Reinforcement learning PyTorch React Tauri
Client-server application for generating draft radiological reports from X-ray images. It supports dataset preparation, model training, validation, and report generation.
Medical AI Transformers FastAPI React
Application for collecting, managing, and modeling adsorption data. It fits theoretical models to empirical isotherms and works with NIST and ARPA-E datasets.
Scientific ML Python RDKit NIST
| Area | Technologies |
|---|---|
| Languages | Python, Java, JavaScript, SQL, Bash |
| ML and deep learning | PyTorch, TensorFlow, Transformers, Hugging Face, LangChain |
| Infrastructure | Docker, Kubernetes, Linux, REST APIs, PostgreSQL |
| Scientific computing | RDKit, NumPy and SciPy, Pandas, NIST databases, ARPA-E |
| Workflow | Git, GitHub Actions, Jupyter, VS Code, IntelliJ, Postman, CI/CD |
- Now: Senior Data Scientist and ML Engineer at Inmatica S.p.A., working on applied AI tools for clinical and scientific workflows.
- Research: PhD in Engineering Sciences at the Vrije Universiteit Brussel, including work on the CheckPack micro-sensor project.
- Foundation: Bachelor's and master's studies in Biotechnology at the University of Genoa.
- Building: Open-source ML tools for clinical research, medical imaging, reinforcement learning, computational chemistry, and LLM workflows.
- Learning: Front-end development and productionizing ML with Rust.
- Looking for: Collaborations involving biotechnology, healthcare, and machine learning.
- Ask me about: Reinforcement learning, medical AI, or moving from biotechnology research into machine learning.